John Beverley

The current COVID-19 pandemic and the previous SARS/MERS outbreaks of 2003 and 2012 have resulted in a series of major global public health crises. We argue that in the interest of developing effective and safe vaccines and drugs and to better understand coronaviruses and associated disease mechenisms it is necessary to integrate the large and exponentially growing body of heterogeneous coronavirus data. Ontologies play an important role in standard-based knowledge and data representation, integration, sharing, and analysis. Accordingly, we initiated the development of the community-based Coronavirus Infectious Disease Ontology in early 2020. As an Open Biomedical Ontology (OBO) library ontology, CIDO is open source and interoperable with other existing OBO ontologies. CIDO is aligned with the Basic Formal Ontology and Viral Infectious Disease Ontology. CIDO has imported terms from over 30 OBO ontologies. For example, CIDO imports all SARS-CoV-2 protein terms from the Protein Ontology, COVID-19-related phenotype terms from the Human Phenotype Ontology, and over 100 COVID-19 terms for vaccines (both authorized and in clinical trial) from the Vaccine Ontology. CIDO systematically represents variants of SARS-CoV-2 viruses and over 300 amino acid substitutions therein, along with over 300 diagnostic kits and methods. CIDO also describes hundreds of host-coronavirus protein-protein interactions (PPIs) and the drugs that target proteins in these PPIs. CIDO has been used to model COVID-19 related phenomena in areas such as epidemiology. The scope of CIDO was evaluated by visual analysis supported by a summarization network method. CIDO has been used in various applications such as term standardization, inference, natural language processing (NLP) and clinical data integration. We have applied the amino acid variant knowledge present in CIDO to analyze differences between SARS-CoV-2 Delta and Omicron variants. CIDO's integrative host-coronavirus PPIs and drug-target knowledge has also been used to support drug repurposing for COVID-19 treatment. CIDO represents entities and relations in the domain of coronavirus diseases with a special focus on COVID-19. It supports shared knowledge representation, data and metadata standardization and integration, and has been used in a range of applications.

COVID-19 often manifests with different outcomes in different patients, highlighting the complexity of the host-pathogen interactions involved in manifestations of the disease at the molecular and cellular levels. In this paper, we propose a set of postulates and a framework for systematically understanding complex molecular host-pathogen interaction networks. Specifically, we first propose four host-pathogen interaction (HPI) postulates as the basis for understanding molecular and cellular host-pathogen interactions and their relations to disease outcomes. These four postulates cover the evolutionary dispositions involved in HPIs, the dynamic nature of HPI outcomes, roles that HPI components may occupy leading to such outcomes, and HPI checkpoints that are critical for specific disease outcomes. Based on these postulates, an HPI Postulate and Ontology (HPIPO) framework is proposed to apply interoperable ontologies to systematically model and represent various granular details and knowledge within the scope of the HPI postulates, in a way that will support AI-ready data standardization, sharing, integration, and analysis. As a demonstration, the HPI postulates and the HPIPO framework were applied to study COVID-19 with the Coronavirus Infectious Disease Ontology (CIDO), leading to a novel approach to rational design of drug/vaccine cocktails aimed at interrupting processes occurring at critical host-coronavirus interaction checkpoints. Furthermore, the host-coronavirus protein-protein interactions (PPIs) relevant to COVID-19 were predicted and evaluated based on prior knowledge of curated PPIs and domain-domain interactions, and how such studies can be further explored with the HPI postulates and the HPIPO framework is discussed.

Basic Formal Ontology (BFO) is a top-level ontology consisting of thirty-six classes, designed to support information integration, retrieval, and analysis across all domains of scientific investigation, presently employed in over 350 ontology projects around the world. BFO is a genuine top-level ontology, containing no terms particular to material domains, such as physics, medicine, or psychology. In this paper, we demonstrate how a series of cases illustrating common types of change may be represented by universals, defined classes, and relations employing the BFO framework. We provide discussion of these cases to provide a template for other ontologists using BFO, as well as to facilitate comparison with the strategies proposed by ontologists using different top-level ontologies.

Current COVID-19 pandemic and previous SARS/MERS outbreaks have caused a series of major crises to global public health. We must integrate the large and exponentially growing amount of heterogeneous coronavirus data to better understand coronaviruses and associated disease mechanisms, in the interest of developing effective and safe vaccines and drugs. Ontologies have emerged to play an important role in standard knowledge and data representation, integration, sharing, and analysis. We have initiated the development of the community-based Coronavirus Infectious Disease Ontology (CIDO). As an Open Biomedical Ontology (OBO) library ontology, CIDO is an open source and interoperable with other existing OBO ontologies. In this article, the general architecture and the design patterns of the CIDO are introduced, CIDO representation of coronaviruses, phenotypes, anti-coronavirus drugs and medical devices (e.g. ventilators) are illustrated, and an application of CIDO implemented to identify repurposable drug candidates for effective and safe COVID-19 treatment is presented.

The COVID-19 pandemic prompted immense work on the investigation of the SARS-CoV-2 virus. Ontologies – structured, controlled, vocabularies – are designed to support consistency of interpretation, and thereby to prevent the development of data silos. This paper describes how ontologies are serving this purpose in the virus research domain, following the principles of the Open Biological and Biomedical Ontology (OBO) Foundry and drawing on the resources of the Infectious Disease Ontology (IDO) Core. We report the development of the Virus Infectious Disease Ontology (VIDO), a reference ontology extending IDO Core covering viral infectious diseases. We examine newly minted terms, showcase ontology term reuse, and illustrate the use of VIDO by annotating selections from recent life science research on SAR-CoV-2, in the interest of supporting machine learning projects.

A clear and provocative introduction to the ethics of COVID-19, suitable for university-level students, academics, and policymakers, as well as the general reader. It is also an original contribution to the emerging literature on this important topic. The author has made it available Open Access, so that it can be downloaded and read for free by all those who are interested in these issues. Key features include: A neat organisation of the ethical issues raised by the pandemic. An exploration of the many complex interconnections between these issues. A succinct case for a continued lockdown until we develop a vaccine. An original account of the Deep Moral Problem of the Pandemic, and a Revolutionary Argument for how we should change society post-pandemic. References to, and engagement with, many of the best writings on the pandemic so far (both in popular media and academic journals). ISBN: 978-0-6489016-0-0

Miranda Fricker's original presentation of Hermeneutical Injustice left open theoretical choice points leading to criticisms and subsequent clarifications with the resulting dialectic appearing largely verbal. The absence of perspicuous exposition of hallmarks of Hermeneutical Injustice might suggest scenarios exhibiting some – but not all – such hallmarks are within its purview when they are not. The lack of clear hallmarks of Hermeneutical Injustice, moreover, obscures both the extent to which Fricker's proposed remedy Hermeneutical Justice – roughly, virtuous communicative practices – adequately addresses the injustice, and the accuracy of criticisms suggesting that Hermeneutical Justice is insufficient to the task. In what follows, after briefly defending necessary and sufficient conditions for what I take to be the best candidate interpretation of Hermeneutical Injustice, I build on recent work on moral responsibility to construct and defend a rigorous explication of Hermeneutical Justice.

Ontologies, as the term is used in informatics, are structured vocabularies comprised of human- and computer-interpretable terms and relations that represent entities and relationships. Within informatics fields, ontologies play an important role in knowledge and data standardization, representation, integra- tion, sharing and analysis. They have also become a foundation of artificial intelligence (AI) research. In what follows, we outline the Coronavirus Infectious Disease Ontology (CIDO), which covers multiple areas in the domain of coronavirus diseases, including etiology, transmission, epidemiology, pathogenesis, diagnosis, prevention, and treatment. We emphasize CIDO development relevant to COVID-19.

The term ‘intelligence’ as used in this paper refers to items of knowledge collected for the sake of assessing and maintaining national security. The intelligence community (IC) of the United States (US) is a community of organizations that collaborate in collecting and processing intelligence for the US. The IC relies on human-machine-based analytic strategies that 1) access and integrate vast amounts of information from disparate sources, 2) continuously process this information, so that, 3) a maximally comprehensive understanding of world actors and their behaviors can be developed and updated. Herein we describe an approach to utilizing outcomes-based learning (OBL) to support these efforts that is based on an ontology of the cognitive processes performed by intelligence analysts. Of particular importance to the Cognitive Process Ontology is the class Representation that is Warranted. Such a representation is descriptive in nature and deserving of trust in its veridicality. The latter is because a Representation that is Warranted is always produced by a process that was vetted (or successfully designed) to reliably produce veridical representations. As such, Representations that are Warranted are what in other contexts we might refer to as ‘items of knowledge’.

If a person requires an organ or tissue donation to survive, many philosophers argue that whatever moral responsibility a biological relative may have to donate to the person in need will be grounded at least partially, if not entirely, in biological relations the potential donor bears to the recipient. We contend that such views ignore the role that a potential donor's unique ability to help the person in need plays in underwriting such judgments. If, for example, a sperm donor is judged to have a significant moral responsibility to donate tissue to a child conceived with his sperm, we think this will not be due to the fact that the donor stands in a close biological relationship to the recipient. Rather, we think such judgments will largely be grounded in the presumed unique ability of the sperm donor to help the child due to the compatibility of his tissues and organs with those of the recipient. In this paper, we report the results of two studies designed to investigate the comparative roles that biological relatedness and unique ability play in generating judgments of moral responsibility in tissue donation cases. We found that biologically related individuals are deemed to have a significant moral responsibility to donate tissue only when they are one of a small number of people who have the capacity to help.

Dilip Ninan has raised a puzzle for centered world accounts of de re attitude reports extended to accommodate what he calls “counterfactual attitudes.” As a solution, Ninan introduces multiple centers to the standard centered world framework, resulting in a more robust semantics for de re attitude reports. However, while the so-called multi-centered world proposal solves Ninan’s counterfactual puzzle, this additional machinery is not without problems. In Section 1, I present the centered world account of attitude reports, followed by the extension to counterfactual attitudes which Ninan targets with his puzzle. In Section 2, I pose the counterfactual puzzle and present Ninan’s multi-centered world solution, emphasizing similarities and differences between multi-centered and centered world accounts of attitude reports. In Section 3, I argue the counterfactual attitude wishing falls under the purview of the multi-centered proposal, but that the proposal generates false predictions for wish reports concerning unsatisfiable content. I canvass responses, ultimately concluding Ninan’s proposal requires substantial revisions.

Do biological relations ground responsibilities between biological fathers and their offspring? Few think biological relations ground either necessary or sufficient conditions for responsibility. Nevertheless, many think biological relations ground responsibility at least partially. Various scenarios, such as cases concerning the responsibilities of sperm donors, have been used to argue in favor of biological relations as partially grounding responsibilities. In this article, I seek to undermine the temptation to explain sperm donor scenarios via biological relations by appealing to an overlooked feature of such scenarios. More specifically, I argue that sperm donor scenarios may be better explained by considering the unique abilities of agents involved. Appealing to unique ability does not eliminate the possibility of biological relations providing some explanation for perceived responsibilities on the part of biological fathers. However, since it is unclear exactly why biological relations are supposed to ground responsibility in the first place, and rather clear why unique ability grounds responsibility in those scenarios where it is exhibited, the burden of proof seems shifted to those advocating biological relations as grounds of responsibility to provide an explanation. Since this seems unlikely, I conclude it is best to avoid appealing to biological relations as providing grounds for responsibility

The Infectious Disease Ontology (IDO) is a suite of interoperable ontology modules that aims to provide coverage of all aspects of the infectious disease domain, including biomedical research, clinical care, and public health. IDO Core is designed to be a disease and pathogen neutral ontology, covering just those types of entities and relations that are relevant to infectious diseases generally. IDO Core is then extended by a collection of ontology modules focusing on specific diseases and pathogens. In this paper we present applications of IDO Core within various areas of infectious disease research, together with an overview of all IDO extension ontologies and the methodology on the basis of which they are built. We also survey recent developments involving IDO, including the creation of IDO Virus; the Coronaviruses Infectious Disease Ontology (CIDO); and an extension of CIDO focused on COVID-19 (IDO-CovID-19).We also discuss how these ontologies might assist in information-driven efforts to deal with the ongoing COVID-19 pandemic, to accelerate data discovery in the early stages of future pandemics, and to promote reproducibility of infectious disease research.